MEDICAL IMAGE FUSION BASED ON QDFT AND CURVELET TRANSFORM

The term fusion means in general an approach to extraction of information acquired in several domains. The goal of image fusion (IF) is to integrate complementary multisensor, multitemporal and/or multiview information into one new image containing information the quality of which cannot be achieved otherwise. The term quality, its meaning and measurement depend on the particular application. The paper presents the image fusion based on Quaternion Discrete Fourier Transform (QDFT) and curvelet transform in and Magnetic Resonance Imaging. In these techniques the MRI image is segmented into sub bands using curvelet transform, the segmented images is then fused into sub bands using QDFT and enhance the image using contourlet transform. So, for better information and higher image resolution on curved shapes we are using wavelet transform with curvelet transform as we know that curvelet transform deals effectively with curves areas, corners and profiles. These two fusion techniques obtaining the minimum errors and present better quality results.The peak signal to noise ratio value for the transform method was higher in comparison to that of existing method fused images. This comparison shows that the quality of fused image was better in transform method